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The quantity and variety of product information available online today has increased significantly in recent years. This situation has exacerbated user information overload perceptions and made it difficult for online shoppers to choose between various online products and services. This is especially true for older adults, who typically have limitations in cognitive abilities due to the natural aging process and, as such, may perceive additional difficulties processing large amounts of information online. In response, Recommendation Agents (RAs) have become popular as decision support tools for online consumers in general, and older adults in particular. However, in the information systems literature, there is a lack of understanding regarding the design of RAs to suit the needs of different segments of the population, including older adults. Grounded in the theory of planned behaviour, and the “aging and IS adoption” literatures, this study investigates the impact of cognitive age and RA comprehensiveness on user perceptions towards the complexity of the input and output stages of an RA, and their subsequent impact on the antecedents of a user’s intention to utilize the RA for online shopping. This experimental study finds that: (i) an individual’s cognitive age significantly increases perceived RA input and output complexity perceptions; (ii) higher levels of RA comprehensiveness increases a user’s RA input and output complexity perceptions significantly; (iii) RA output complexity plays a more critical role than RA input complexity in shaping user perceptions of the overall complexity of an RA; and, (iv) increased levels of RA comprehensiveness increases individual perceptions of RA usefulness. Additionally, and as expected, cognitive age moderates the relationship between RA comprehensiveness and input/output complexity such that the effect is stronger for older adults. Surprisingly, however, cognitive age also moderates the relationship between RA comprehensiveness and perceived RA usefulness such that it is stronger for older adults. Theoretically, this study helps us to better understand how different levels of RA comprehensiveness, in terms of both the input and output stages of the RA operation, impact the intention of users of different cognitive ages to use online RAs. For practitioners, the results highlight the importance of customizing the design of RAs, in both their input and output stages, for consumers with different cognitive ages.

Thesis

Doctor of Philosophy (PhD)

Advisors/Committee Members: Hassanein, Khaled, Business.

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This research explores hacker motivation, demotivation and task selection through the lenses of the Theory of Reasoned Action (TRA) and General Deterrence Theory (GDT). The research also explores how context surrounding individual and task characteristics affects a hacker’s decision making process in selecting a hacking task. To build a solid foundation on which to understand and combat threats to information systems, researchers need to look past the technical issues of data security and explore why hackers do what they do. This research addresses this gap by understanding why hackers identify and assess hacking tasks. It is hoped that by investigating the motivations of these highly skilled Information Systems (IS) users, new insights into how to avoid becoming a hacker target might be developed. Participants in this study were individuals who self-identify as hackers. They completed a survey to validate the proposed model and answered open-ended questions to provide further insights. The quantitative data was analysed using Structured Equation Modelling; classical content analysis was conducted to examine the qualitative data. This research was successful in identifying the role of TRA and GDT in hacker task selection. The research confirmed the importance of mastery, curiosity, and task complexity in a hacker's evaluation process and provided enticing clues for further research into the role of task complexity in a hacker’s task evaluation process. The research also confirmed that subjective norms play an important part in shaping behavioural intentions towards engaging in a hacking task. Additionally, a clear linkage was identified between perceived certainty of sanction and behavioural intention. Contributions of this research to both academia and practice are outlined as well as potential limitations and areas for future research.

Dissertation

Doctor of Philosophy (PhD)

This research explores hacker motivation, demotivation and task selection through the lenses of the Theory of Reasoned Action (TRA) and General Deterrence Theory (GDT). The research also explores how context surrounding individual and task characteristics affects a hacker’s decision making process in selecting a hacking task. To build a solid foundation on which to understand and combat threats to information systems, researchers need to look past the technical issues of data security and explore why hackers do what they do. This research addresses this gap by understanding why hackers identify and assess hacking tasks. It is hoped that by investigating the motivations of these highly skilled Information Systems (IS) users, new insights into how to avoid becoming a hacker target might be developed. Participants in this study were individuals who self-identify as hackers. They completed a survey to validate the proposed model and answered open-ended questions to provide further insights. The quantitative data was analysed using Structured Equation Modelling; classical content analysis was conducted to examine the qualitative data. …

Advisors/Committee Members: Head, Milena, Business Administration.

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In this dissertation, we study several quantitative approaches centered on supply chain management, sustainability development, performance measurement frameworks, and environmental regulation mechanisms. The topic of sustainability has been of great interest for the past few years in academia. Many governments also have taken actions to incentivize firms to reduce their negative environmental and social impacts. It is unclear, however, how successful policy makers have been in reducing the sustainability threats. This raises the question of ``how can policy makers play an effective role in helping businesses become more sustainable, while complying with entrepreneurs and investors' expectations?'' This dissertation is organized on the basis of six chapters. Having reviewed the literature and research directions of sustainable supply chain management in Chapter 1, we present a review of sustainability performance measurement frameworks in Chapter 2. In addition to proposing a framework to assess sustainability efficiency in supply chains, we discuss research questions with a focus on the social aspect of sustainability development. In Chapter 3, we develop a two-stage data envelopment analysis model with an application to the energy sector. This approach measures relative efficiencies of a number of comparable decision makers and does not require predetermined weights of indicators. We relax some restricting assumptions used in previous studies and obtain a nonlinear problem, for which we develop a solution method. Chapter 4 investigates a more general multi-stage assessment framework that monitors suppliers, manufacturers, distributers, and retailers' sustainable practices. The major finding is developing a multi-stage data envelopment analysis to measure supply chains' sustainability efficiency. In Chapter 5, we investigate market-based schemes with a focus on curbing pollution emitted by business entities and develop a game-theoretic formulation. Finally, we summarize the major contributions of this dissertation and future research directions in Chapter 6.

Thesis

Doctor of Philosophy (PhD)

Advisors/Committee Members: Hassini, Elkafi, Business.

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With the increasing prevalence of chronic disease throughout the world, electronic Personal Health Records (ePHRs) have been suggested as a way to improve chronic disease self-management. However, ePHRs are not yet widely used by consumers. Protection Motivation Theory (PMT) has been successfully used to explain health related behaviours among chronic disease patients. In addition, Information Systems (IS) theories such as Task Technology Fit (TTF) have been successfully used to explain information technology adoption. This study combines PMT with Perceived Task Technology Fit (PTTF) and the health self-management readiness concept of the Patient Activation Measure (PAM) to propose a research model which will aid in the understanding of ePHR adoption by chronic disease patients. The role of educational interventions on various elements of the proposed model is also examined. A survey-based study of 230 participants is used to empirically validate the proposed model via structural equation modeling techniques. Results reveal that the PMT constructs, as well as PTTF and PAM all have significant direct or indirect effects on the intention to adopt an ePHR. In addition, the educational intervention analysis indicates that the provision of advanced ePHR education positively influences various constructs in the model, while the use of fear appeals through Diabetes complication education does not have an effect.

Doctor of Philosophy (PhD)

Advisors/Committee Members: Hassanein, Khaled, Business.

▼  This thesis contains two parts. In the first part, which contains Chapter 2 and Chapter 3, we consider scheduling problems with learning effect and time-dependent processing time on a single machine. In Chapter 2, we investigate the earliness-tardiness objective, as well as the objective without due date assignment consideration. By reducing them to a special linear assignment problem, we solve them in near-linear time. As a consequence, we improve the time complexity for some previous algorithms for scheduling problems with learning effect and/or time-dependent processing time. In Chapter 3, we investigate the total number of tardy jobs objective. By reducing them to a linear assignment problem, we solve them in polynomial time. For some important special cases, where there is only learning effect OR time-dependent processing time, we reduce the time complexity to quadratic time. In the second part, which contains Chapter 4 and Chapter 5, we investigate the bicriteria scheduling problems in a supply chain. We separate the objectives in two parts, where the delivery cost is one of them. We present efficient algorithms to identify all the Pareto-optimal solutions for various scenarios. In Chapter 4, we study the cases without due date assignment; while in Chapter 5 we study the cases with due date assignment consideration. Advisors/Committee Members: Steiner, George, Business.

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This thesis explores three important issues in financial distress and corporate bankruptcy: bankruptcy venue choice and creditor recovery, the efficiency of Chapter 11 corporate bankruptcy and distressed exchanges, and the bankruptcy ripple effect on peer firms’ investment policy.

Dissertation

Doctor of Philosophy (PhD)

This thesis explores three important issues in financial distress and corporate bankruptcy: bankruptcy venue choice and creditor recovery, the efficiency of Chapter 11 corporate bankruptcy and distressed exchanges, and the bankruptcy ripple effect on peer firms’ investment policy.

Advisors/Committee Members: Miu, Peter, Business.

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Knowledge sharing–the dissemination of knowledge from an individual/group to another–has been an interesting topic for knowledge management scholars. Previous studies on knowledge sharing in online communities have primarily focused on communities of practice (organizational/business communities) and the social factors of knowledge sharing behaviour. However, non-business-oriented online communities have not been rigorously examined in the academic literature as venues for facilitating knowledge sharing. In addition, the burst of new age Internet tools (artifacts) such as social bookmarking has changed the face of online social networking. Within the context of Web 2.0, this socio-technical research investigation introduces both social and technical factors affecting attitude towards knowledge sharing in communities of relationship and communities of interest, and proposes a relational model of knowledge sharing attitude in Web 2.0 online communities. Social Capital Theory provides the main theoretical backbone for the proposed model. Theory of Reasoned Action (TRA) and social constructionsim have also been used. Following the description of the proposed hypotheses and research methodology using a survey about three Web 2.0 websites (Facebook, LinkedIn, and Cnet), data analysis through Partial Least Squared (PLS) method is applied to examine the effect of social and technical antecedent of knowledge sharing attitude. The R2 value of 0.78 indicates the strong explanatory power of the research model.

Dissertation

Doctor of Philosophy (PhD)

Advisors/Committee Members: Head, Milena, Business Administration.

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The importance of the environmental agenda has been rising exponentially in recent years. Firms face mounting pressure from multiple stakeholder groups to respond to environmental concerns. In a quest for ‘greener’ businesses, many companies increasingly rely on inter-firm strategic partnerships. Despite growing popularity among practitioners, green partnerships still remain a poorly understood phenomenon. The questions of how value is created in green partnerships, what factors drive their performance and what short-term and long-term implications of green partnerships are, still wait to be explored. In this dissertation, the topic of value creation in green strategic partnerships is analyzed in a two-step project. Study 1 examines the financial outcomes of inter-firm green strategies by exploring variations in stock market valuation of green strategic partnerships across multiple industries and functional domains. Study 2 focuses on the innovation-related outcomes by examining firm green patenting activities in the context of inter-firm networks in the chemical industry. Three complementary theoretical perspectives are utilized: corporate social responsibility (CSR) literature, organizational capabilities and social networks analysis. Data is collected based on extensive archival search of multiple sources. The major insight from this dissertation is that green strategic partnerships can be instrumental in unlocking value creation potential of a firm, but this phenomenon does not always happen and not for every firm. Financial implications of green partnerships vary depending on the functional domain of a partnership, a history of a firm’s environmental performance and the environmental profile of the industry. Green technology partnerships indeed enhance firm green innovation, as reflected in a greater number of successful green patent applications, but they do so at the level of firm networks, not at the level of the industry network. The properties of knowledge resources such as breadth of knowledge pool, knowledge compatibility, and knowledge specificity (green versus non-green), accumulated in a firm network do affect firm propensity to achieve green innovation. The structural properties of networks influence firm green innovation only at the firm network level. More specifically firm network density is positively related to firm green innovation. At the industry network level, however, none of the explored structural properties such as global network reach, global network clustering, and global network transitivity, have any impact on firm green innovation.

Dissertation

Doctor of Philosophy (PhD)

Advisors/Committee Members: Pujari, Devashish, Business Administration.

▼ This thesis explores three important topics spanning international asset pricing, empirical capital structure, U.S. politics, and corporate law: relationship-specific investment (RSI), contracting environment and financial performance; RSI, contracting environment and the choice of capital structure; and political value and SEC enforcement actions. Firms that engage in long-term bilateral relationships with their buyers or suppliers are usually required to make relationship-specific investments. We examine how the values of these long-term specific investments are affected by the quality of governmental contract enforcement. We find that firms in relationship-specific industries have higher valuations, measured by Tobin’s Q, when their countries of origin are able to strongly enforce contractual agreements. Our finding is robust to a variety of empirical specifications and regression methods. We also show that as legal quality improves, firms with relationship-specific investments exhibit lower operating performance, presumably due to risk or in order to motivate further investments from their stakeholders. Further analysis of the cross-section of stock returns supports a risk-based explanation. Firms in long-term bilateral relationships with their customers or suppliers are required to make relationship-specific investments in the form of physical equipment, human resources, specific production sites, or brand names. These dedicated assets are usually tied to a particular use or relationship and cannot be redeployed if the firm is liquidated. In the absence of legal enforcement, firms are required to limit their use of debt financing and, consequently, signal a reduced default risk to encourage investment by their contracting parties. Using a sample of 143,278 firm-year observations, and measures of industry-level relationship-specificity and the quality of legal enforcement across 57 countries, we find strong evidence that good quality contract enforcement mitigates the negative association between relationship-specificity and debt financing. The Securities and Exchange Commission (SEC) plays a central role in investigating potential violations of securities laws and initiating enforcement actions in the United States. We examine the association between political culture and political connections and the penalties imposed at the end of SEC enforcement actions. Our analysis is based on two key ideas. First, the political culture of a firm indicates its ethical boundaries and explains the propensity of misconduct across different domains, such as securities laws. Second, political connections signal a firm’s willingness to challenge SEC’s enforcement decisions. We find that the individual defendants associated with Republican firms are less likely to receive a bar or suspension penalty. This finding supports the notion that Republican managers are less likely to commit securities fraud since the Republican ideology stresses market discipline. Moreover, in line with prior research, our results show that political… Advisors/Committee Members: Chamberlain, Trevor, Business.

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This dissertation contains three essays on the predictability of asset returns and its implications. All essays contain tests and applications that could be implemented in real time, and a summary of economic and statistical significance. The dissertation as a whole adds to the growing literature that returns can be predictable, enough so to provide economically significant differences in returns. The same applies to predicting market returns, or market timing. The first essay modifies a popular measure of investor sentiment (Baker and Wurgler, 2006) with the idea in mind that market-wide sentiment will partially reverse itself in the next period. Economic fundamentals are removed to provide a more pure measure of sentiment, which is found to predict returns better (with sentiment having a negative relationship with market returns), resulting in a better investment strategy. The second essay implements a statistical methodology which allows many predictors (portfolio returns) to be aggregated into a composite index. This index predicts returns well, and also gives insight into why two well-observed stock market anomalies, size and value premiums, may occur: they predict future market returns and are therefore an ICAPM state variable that reflects future wealth opportunities. For this reason they carry a risk premium. The third essay provides a new forecasting approach that imposes the restrictions of the popular arbitrage pricing theory (APT) on an existing statistical approach (principal components analysis). The result is that the expected returns of asset positions hedged against systematic risk are better estimated, and average error is greatly reduced out-of-sample.

Thesis

Doctor of Philosophy (PhD)

Advisors/Committee Members: Balvers, Ron, Business Administration.

▼ This thesis aims to develop a deeper understanding of entrepreneurship education as a type of entrepreneurship support. We study the overall entrepreneurship support systems, the pedagogical models developed for students with different level of entrepreneurship experience, and the long-term influences of entrepreneurship education on students. Entrepreneurship education and training has become very popular in universities, colleges, and business development centers world-wide, and has been of great interest in academia also. However, the entrepreneurship teaching is usually not informed by solid theories, and students’ different learning needs are not taken into consideration. In addition, the long-term influences of entrepreneurship education on students are unclear. This thesis consists of four manuscripts, each of which is a co-authored paper that presents an individual study. Study 1 is a comprehensive literature review of 122 journal articles that disentangles multiple conceptualizations used to research entrepreneurship support and examines the effectiveness of each source and type of support. We present our theorizations found and explore how three prevailing management theories could motivate theoretical refinements in the field. We also identify areas for future research and offer guidance on how to improve the relevance of entrepreneurship support studies. Study 2 develop a set of conceptual models anchored in learning theory regarding how entrepreneurship education should be taught to students. These conceptual models are built on the techniques of entrepreneurship pedagogy such as experiential learning. They are developed for three groups of students: students without any entrepreneurship experience, students with previous entrepreneurship experience, and students who are currently running their start-ups. A set of potential variables that could be used for course evaluation purposes is also included. Choosing a model pertinent to students’ attributes, lecturers could hence design entrepreneurship courses suitable for the students. This study also provides novel insights into educators’ design of entrepreneurship programs. Study 3 is an approximately four-year quantitative longitudinal study examining the stability of students’ attitude, perceived behavior control, subjective norm, and intention to entrepreneurship over time, and the role of entrepreneurship education in this process. Findings have implications for interpreting extant entrepreneurial literature, and policy and practice related to nascent entrepreneurship development and support. The results support our argument that the theoretical and practical value of entrepreneurship literature should hinge on the temporal stability of the attitudinal and intentional constructs used. Study 4 is a qualitative study exploring what are the important knowledge/skills students learned from the entrepreneurship courses they took on average five years previously, which pedagogical approach seems most effective, whether the courses are… Advisors/Committee Members: Honig, Benson, Business Administration.

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This thesis proposes several new and useful financial econometric tools to facilitate risk analysis, portfolio choice and forecasting. This thesis starts with an introduction in Chapter 1. The research background, motivation and the structure of the thesis are illustrated in this chapter. Chapter 2 proposes a class of models that jointly model returns and ex-post variance measures under a Markov switching framework. Both univariate and multivariate return versions of the model are introduced. Estimation can be conducted under a fixed dimension state space or an infinite one. The proposed models can be seen as nonlinear common factor models subject to Markov switching and are able to exploit the information content in both returns and ex-post volatility measures. Applications to equity returns compare the proposed models to existing alternatives. The empirical results show that the joint models improve density forecasts for returns and point predictions of return variance. Using the information in ex-post volatility measures can increase the precision of parameter estimates, sharpen the inference on the latent state variable and improve portfolio decisions. Chapter 3 offers a new exact finite sample approach to estimating ex-post variance using Bayesian nonparametric methods. Until now ex-post variance estimation has been based on infill asymptotic assumptions that exploit high-frequency data. In contrast to the classical counterpart, the proposed method exploits pooling over high frequency observations with similar variances. Bayesian nonparametric variance estimators under no noise, heteroskedastic and serially correlated microstructure noise are introduced and discussed. Monte Carlo simulation results show that the proposed approach can increase the accuracy of variance estimation. Applications to equity data and comparison with realized variance and realized kernel estimators are included. Chapter 4 extends the third chapter to estimate the ex-post covariance matrix of asset returns from high-frequency data. As before, pooling is used to improve estimation accuracy and the method does not rely on infill asymptotic assumptions. In addition, the proposed covariance estimator is guaranteed to be positive definite. Furthermore, a new synchronization method of observations based on data augmentation is introduced. The Bayesian estimator is made robust to independent microstructure noise and nonsynchronous trading. According to Monte Carlo simulations, the new estimator is very competitive with existing estimators. Empirical applications evaluate the new estimator from an economic perspective. Finally, Chapter 5 concludes and summarizes the contribution of this thesis to the literature.

Thesis

Doctor of Philosophy (PhD)

Advisors/Committee Members: Maheu, John, Business.

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This dissertation contains three essays on the non-pecuniary preferences pertaining to financial asset characteristics and their implications for asset pricing. The first essay considers the pricing implications of screens adopted by socially responsible investors. A model including such investors reconciles the empirically observed risk-adjusted sin-stock abnormal return with a systematic “boycott risk premium” which has a substantial financial impact that is, however, not limited to the targeted firms. The boycott effect cannot be displaced by litigation risk, a neglect effect, and liquidity considerations, or by industry momentum and concentration. The boycott risk factor is valuable in explaining cross-sectional differences in mean returns across industries and its premium varies directly with the relative wealth of socially responsible investors and with the business cycle. The second essay generalizes Fama (1996)’s concept of Multi-Factor Efficiency without being limited by additional random state variables that must affect future investment opportunities. Incorporating non-pecuniary preferences into a representative investor’s utility function generates multi-factor pricing implications. A representative investor chooses among expected returns, variances, and levels of characteristics according to their taste, which gives rise to an N-fund separation theorem with static characteristics. If a portfolio is built to maximize the exposure to the asset characteristics, the covariance between asset returns and this portfolio returns will be identical to the underlying characteristics. Such identity makes obsolete any attempts to distinguish between characteristics and risk exposures as the driving forces behind the cross-sectional variation in stock returns. The third essay develops a procedure for deriving systematic factors from characteristics, based on maximizing each factor’s exposure to a characteristic subject to a given level of factor variance. The resulting characteristic-mimicking portfolios (CMP) price mean asset returns identically as the original characteristics, irrespective of the underlying model. Accordingly, differences in the performance of mimicking factors and characteristics in explaining mean returns should be interpreted as an artifact of arbitrary procedural choices for generating mimicking factors. Factors and characteristics may be distinguished usefully only by determining if CMPs have significant explanatory power for the time series of returns.

Thesis

Doctor of Philosophy (PhD)

Advisors/Committee Members: Balvers, Ronald, Business.

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This thesis investigates three important issues on bank financial reporting quality: 1) the impact of banks’ retail versus wholesale funding structure on their earnings quality, 2) the implications of economic and monetary policy uncertainty for banks’ earnings opacity, and 3) the relationship between banks’ bad time history and accounting conservatism. In the first essay, we examine the implications of banks’ funding strategies for banks’ earnings quality. We find that banks’ greater reliance on retail deposits over wholesale funds is negatively and significantly associated with the magnitude of earnings management through discretionary loan loss provisions, the likelihood of meeting-or-beating earnings benchmark, and the extent of income smoothing through loan loss provisions. This finding is consistent with the arguments that retail deposits are relatively more stable and information-insensitive, represent a more conservative business model, and attract more intensive monitoring from the Federal Deposit Insurance Corporation (FDIC) than wholesale funds, thereby improving banks’ financial reporting quality. In the second essay, we investigate whether economic and monetary policy uncertainties affect banks’ earnings opacity. When economic and monetary policies are relatively uncertain, it is easier for bank managers to distort financial information, as unpredictable policy changes make assessing the existence and impact of hidden “adverse news” more difficult for investors and creditors. Policy uncertainty also increases the fluctuation in banks’ earnings and cash flows, providing additional incentives for bank managers to engage in earnings management. Our results show that uncertainty in economic and monetary policy is associated with greater magnitude of discretionary loan loss provisions, higher likelihood of just meeting-or-beating the prior year’s earnings, and lower levels of accounting conservatism, suggesting that economic and monetary policy uncertainties lead to higher banks’ earnings opacity. In the third essay, we examine the impact of banks’ bad times on the conservatism of accounting policy. Specifically, we investigate two types of bad times: banks’ own past experiences of undercapitalization and their experiences of witnessing the failures of other banks in state-wide and county-wide crises. We find that both types of banks’ bad times are positively related to timelier recognition of earnings decreases versus earnings increases in accounting income. We also find that following exposure to bad times, banks increase their allowance for loan losses. Collectively, our results suggest that bank-specific bad times and macro-level banking crises lead to greater bank accounting conservatism. These findings support the arguments that banks exposed to past crises overweight their bad time history, and become more cautious and pessimistic about their future earnings performance and loan quality.

Thesis

Doctor of Philosophy (PhD)

Advisors/Committee Members: Jin, Justin, Business.

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This dissertation takes a sharp methodological turn from prior research on religiousness, spirituality, and culture in organizations by making advances in the study of the structure and role of workplace religio-spiritual beliefs, combining a critical review, theory building, and two empirical sections. The research is based on the premise that the study of individual psychology has yet to address the cross-cultural and domain-specific nature of religio-spiritual beliefs that come to mind naturally in everyday work situations. First, after a case is made for the study of religio-spiritual beliefs, a critical review of the literature provides a comparison of 90 content-based measurement models, and is followed by implications for improving future measurement and research. Second, a conceptual discussion recommends a way forward for a domain-specific conceptualization of religiousness and spirituality and sets a framework for improving methodology, drawing from grounded theory, integral theory, and sense-making methodology. Third, a bottom-up exploration of the religio-spiritual beliefs induced by a variety of workplace situations is conducted through interviews of informants from six major faith traditions, plus the spiritual-but-not-religious. From the analysis, workplace situations, associated beliefs, and mental modules are structured according to the four quadrants of the Workplace Integral Model, each quadrant typified by a different workplace-grounded existential dilemma. Fourth, a higher level of religio-spiritual cognition is accessed through a sense-making methodology, revealing why and how work-related thoughts, self-concepts, and experiences become imbued with religio-spiritual significance, as illustrated in eight modes arranged on a Religio-Spiritual Sense-Making Circumplex. It is hoped that these findings can help set a foundation for future progress with research methods, measurement models, and theory building focused on the religio-spiritual thoughts of a diversity of people in the workplace.

Thesis

Doctor of Philosophy (PhD)

Advisors/Committee Members: Hackett, Rick D., Business.

▼ This thesis examines three important topics in empirical finance: The nonparametric conditional beta, the propagation of risks between markets, and the predictability of the market return density using economics and financial variables. First, I introduce a model that links the conditional beta to the second order conditional moments of returns. A key insight of my approach is that if the joint distribution of stock returns and market returns are correctly specified, then it follows that their contemporaneous pricing relationship is completely determined by the associated conditional distribution. The model that I propose is able to study the effects of a big shock in the market on the beta of an individual stock or a portfolio. This approach allows the beta to be a flexible function of the sign and size of the market portfolio which is absent in the finance literature. My results demonstrate that beta does depend on the market portfolio in a nonlinear manner. This carries implications for systematic risk measurement significantly different than what we have in a fixed parametric model. My model nests the Gaussian and Student-t distribution as special cases but importantly allows for deviations from the elliptic family of distributions. This includes asymmetric distributions. I extend the model to include more assets and provide a test to see if other factors are priced. My empirical results illustrate that in the event of big shocks in the market the firm's beta coefficient can go down or shoot up, depending on the market conditions (volatility). Second, I extend the literature on the spillover effects or contagion effects that focus on the transmission of shocks through moments to spillover effects on the conditional density and seek to shed greater light on the contemporaneous information transmission between markets. The objective is to develop a joint model of returns on two different markets governed by an in infinite mixture model from which the conditional density of the first market given the returns of the other market can be derived. This enables us to study how a shock in one market influences the contemporaneous and future (one-day-ahead, one-week-ahead, and one-month ahead) conditional density of the other market. This makes it possible to explore the contemporaneous spillover effects of big shocks in one market on various features of the density of the other market such as conditional expected return, volatility, skewness and kurtosis, and value at risk. Third, I investigate the predictability of the market return density using financial and macroeconomic variables. The objective is to develop a Bayesian nonparametric model of the distribution of market returns where the weights of the mixture change over time. Available information on financial and macroeconomic variables is employed to predict the weights of the mixture components in the predictive density of market returns over time. This permits the density of market returns to be unknown and to change over time. Moreover, the proposed model… Advisors/Committee Members: Maheu, John, Business Administration.

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Railroad transportation of hazardous materials (hazmat) has grown significantly in recent years in Canada. Although rail is one of the safest modes for hazmat transport, the risk of catastrophic events such as the Lac Mégantic train disaster, does exist. In this thesis, we study a number of measures to manage and mitigate the risk associated with rail hazmat shipments. First, we propose a methodology that makes use of analytics to dis-aggregate national freight data to estimate hazmat traffic on rail-links and at rail-yards in Canada. Further, a focused analysis is conducted on crude oil rail shipments to develop long-term forecasts and evaluate the impact of proposed pipeline projects. Second, we present an emergency response planning problem, aimed at the effective and efficient response to rail hazmat incidents. A two-stage stochastic programming problem is solved over part of the Canadian railroad network, which provides recommendations on where to locate response facilities, and which equipment packages to stockpile at each facility. Finally, we study infrastructure investment as a strategy to mitigate the risk associated with rail hazmat shipments. This strategy is based on building new railway tracks to provide alternative routes to the riskiest parts of the network. Given the hierarchical relationship between the decisions made by regulatory agencies and railroad companies, a bilevel programming approach is used to identify the optimal set of infrastructure investment options given an allocated budget. Our computational experiments show that significant network-wide risk reduction is possible if hazardous shipments are routed using some of the proposed alternative rail tracks.

Thesis

Doctor of Philosophy (PhD)

Advisors/Committee Members: Verma, Manish, Business.

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In this thesis, we study three periodic-review, finite-horizon inventory systems in the presence of supply and demand uncertainties. In the first part of the thesis, we study a multi-period single-station problem in which supply uncertainty is modeled by partial supply. Formulating the problem under a robust optimization (RO) framework, we show that solving the robust counterpart is equivalent to solving a nominal problem with a modified deterministic demand sequence. In particular, in the stationary case the optimal robust policy follows the quasi-(s, S) form and the corresponding s and S levels are theoretically computable. In the second part of the thesis, we extend the RO framework to a multi-period multi-echelon problem. We show that for a tree structure network, decomposition applies so that the optimal single-station robust policy remains valid for each echelon in the tree. Furthermore, if there are no setup costs in the network, then the problem can be decomposed into several uncapacitated single-station problems with new cost parameters subject to the deterministic demands. In the last part of the thesis, we consider a periodic-review Assemble-To-Order (ATO) system with multiple components and multiple products, where the inventory replenishment for each component follows an independent base-stock policy and product demands are satisfied according to a First-Come-First-Served (FCFS) rule. We jointly consider the inventory replenishment and component allocation problems in the ATO system under stochastic component replenishment lead times and stochastic product demands. The problems are formulated under the stochastic programming (SP) framework, which are difficult to solve exactly due to a large number of scenarios. We use the sample average approximation (SAA) algorithms to find near-optimal solutions, which accuracy is verified by the numerical experiment results.

Thesis

Doctor of Philosophy (PhD)

Advisors/Committee Members: Huang, Kai, Business.

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Social commerce has emerged as a new platform that enables users to conduct shopping assisted by inputs from other members and to publicly comment on transactions or products. It therefore adds a social aspect to traditional online commerce environments. Nevertheless, the role of the social facet embedded in such transactions in influencing user behaviors is not fully understood. In this dissertation, I develop three empirical studies to better understand social commerce user behaviors and to specifically consider the biasing factors that exist in these social platforms and can skew user rational decision-making. The results of these studies highlight the importance of social context in influencing users’ behaviors. The first study’s results show the role of interactions among social commerce users in affecting users’ decisions. The second study shows that like most of social networking sites; the use of social commerce platforms are prone to become habitual. Furthermore, this study shows how the developed habit among users can influence their rational purchasing decision. Finally, the third study explores the role of group identification and it shows that social identity that will be developed among members can cause some bias and skew the rational behaviors of users.

Thesis

Doctor of Philosophy (PhD)

Advisors/Committee Members: Yuan, Yufei, Business.

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Security breach disclosure is the public disclosure of information regarding a data security incident. It allows organizations to communicate salient information to the affected parties and stakeholders regarding the nature and impact of the breach, and remediating solutions undertaken regarding the breach. Recent cases of large-scale security breaches have revealed that security breach disclosure remains a challenging subject for policymakers, practitioners, and researchers. There is a lack of understanding and consensus on what breaches need to be disclosed and little evidence on how actual practices are employed. Using an adapted grounded theory methodology that combines computerized textual extraction and ground theory coding techniques, this study explores relevant issues through four research questions with distinct objectives that would enhance understanding of the issues in public breach disclosure. First, recent regulations from the US, EU, and Canada are reviewed to identify the core elements in breach disclosure. Second, this study develops methods to extract information content from disclosures. Third, matrices and measuring instruments are developed to evaluate the quality, and last, a framework is proposed to map out the paths and directions for future research. These advancements lay the crucial groundwork in the field of security breach disclosure and will contribute greatly towards future policies, practice, and research. The expected societal significance of this research is profound. The research is relevant to practitioners, regulators, and the information security community as it provides valuable insight on current challenges and future directions. The ultimate goal is to strengthen our understanding of security breach disclosure and enhance the accumulation and transfer of knowledge obtained through security breach disclosure; thereby providing organizations, regulators, and the information security community with the information necessary to develop policies, tools, and controls for identifying, managing, and reducing the risks of future security incidents. The proposed core elements, methods of extracting relevant information content, quality evaluation matrices, and framework mark a significant advancement towards this vision.

Thesis

Doctor of Philosophy (PhD)

Recent cases of security breach at Equifax, Yahoo, and Uber have raised attention from the public and regulators on the issues of public disclosure of security incidents. However, the lack of understanding and research in security breach disclosures has hampered our ability in defining what needs to be disclosed, understanding what are actually disclosed, and determining how well the incidents are disclosed. These issues are urgent and important thus warrant considerable efforts to carefully examine the current landscape of policy and practice, and to provide methods to evaluate disclosures so that meaningful advancements in research and improvements in practice can be made. This study recommends a set of…

Advisors/Committee Members: Yuan, Yufei, Business Administration.

▼ This thesis investigates three important topics on financial reporting and information environment: 1) the timing of patent disclosure and its effect on the cost of equity capital; 2) how CEO mobility affects innovation through changes in firm information environment and incentive structure, and 3) how variability of tort law at the state level affects financial reporting opacity. In a natural experiment setting, the first essay shows that early disclosure of patent information reduces firms’ cost of equity capital. A notable feature of the American Inventors Protection Act (AIPA) is used, which separates the patent publication date from its grant or issue date. Using this feature as an exogenous shock, it is posited that patent disclosure choice in the patent application influences firms’ information environment by signaling firm’s proprietary information. Consistent with extant disclosure literature, this essay finds that early patent disclosure around the exogenous shock of regulatory change is associated with reduction in implied cost of equity capital. In light of scant prior literature on timing of patent disclosure, this essay offers empirical evidence that benefits of early patent disclosure outweigh the costs. This is the case even after adjusting for a real option to delay inherent in the AIPA. To exclude alternative explanations, I run a battery of robustness and sensitivity tests and the results of early patent disclosure still hold. This essay provides new evidence on the timing of proprietary disclosure that is of practical significance and importance to investors, policy makers, and regulators. Using Inevitable Disclosure Doctrine (IDD) as an exogenous shock, the second essay provides direct evidence of how external CEOs increase technology spillover and spur innovation. In particular, two channels which have received theoretical support from extant literature are examined. The first channel is technology spillover and the second one is income inequality. My results show that external CEOs, relative to internal CEOs, increase both technology spillover and income inequality. Moreover, I find direct causal evidence linking the technology spillover with innovation. On the other hand, I do not find similar evidence for income inequality. My results remain substantially unchanged for alternative measures of technology spillover and identification strategies. I also find that CEO’s industry origin is an important factor. Specifically, CEOs from the same or similar industries drive the results. In the third essay, I examine how the changes in U.S. state-level liability regimes affect the firm-level financial reporting opacity in the US banking industry. Using tort reform as an exogenous shock, it is found that banks located in states adopting tort reforms have more opacity (greater earnings management) than those located in non-adopting states. Further analyses suggest that banks in the adopting states also smooth earnings more than those in the non-adopting states. I conduct additional analyses to test for… Advisors/Committee Members: Nainar, Khalid, Business Administration.

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Hazardous materials (hazmat), such as crude oil and gasoline, are harmful to humans and the environment because of their toxic ingredients, but their transportation is integral to sustain our industrial lifestyle. In North America, a significant portion of hazmat shipments is moved via the railroad network. Rail hazmat incidents are rare though the consequences could be catastrophic. The low probability–high consequence nature of such events mandate that a risk-averse plan be implemented for routing hazmat shipments. We propose a value-at-risk (VaR) and conditional value-at-risk (CVaR) methodology to route rail hazmat shipments, using the best train configuration, over a given railroad network with limited number of train services, such that the transport risk is minimized. Freight train derailment records of the Federal Railroad Administration (FRA) were analyzed to model the behavior of railroad accidents, and to estimate their conditional probabilities. The proposed methodologies were used to study several problem instances generated using the realistic network of a railroad operator in Midwest United States, and to demonstrate that they are superior to the existing risk measures in the literature in regard to providing risk-averse routing of hazmat shipments and being versatile enough to yield various routes based on the risk preferences of decision makers. Next, we propose a CVaR model, as a risk-averse routing plan for multiple rail hazmat shipments and multiple origin-destinations pairs, such that the total transport risk in the railroad network as measured by CVaR is minimized. However, it may happen that certain links and yards of the railroad network tend to be overloaded with hazmat traffic and risk. To overcome this issue, we also promote equity in the spatial distribution of risk. Therefore, the main problem is to find minimum risk routes, while limiting and equitably spreading the risk in any zone where the railroad network is embedded. The problem is mathematically formulated, and a heuristic algorithm is proposed for its solution, which takes into consideration the risk load limits on arcs and transferring yards and spreads the risk equitably throughout the network. Moreover, a lower bound based on a Lagrangian relaxation of the mathematical formulation is also provided. Finally, several computational experiments are developed using the above realistic railroad network.

Thesis

Doctor of Philosophy (PhD)

Advisors/Committee Members: Verma, Manish, Business.

▼ The exponential growth of crowdfunding over the past 10 years signals its evident importance as an alternative method of marketing and funding innovation. Because of the arm’s length relationship between innovators and their backers in this system, signaling quality of the project is vital for success of a campaign. Backers mainly make decisions based on quality signals they receive, and because the average spatial distance between them and innovators is substantial in a crowdfunding setting, this (together with the effectiveness of quality signals) has consequences on the relationship between them. In this modern setting, the type of signals used by campaign owners differs from the traditional costly signals of quality. Due to the relatively small size of crowdfunding projects, and the small investments made by each backer, innovators provide less costly and rhetorical quality signals, which have become a topic of academic inquiry in this field. In this dissertation, I conducted two studies to investigate important aspects of crowdfunding. First, I studied geographic distance and its interaction with quality signals (both costly and less costly signals). I argue that that the information gap between backers and innovators rises with the increase of geographic distance. Drawing on signaling theory, I argue that since distant backers face higher levels of information disadvantage (compared to nearby backers), the value and importance of quality signals are amplified for them. I find support for my proposition that quality signals used to reduce the information gap between two sides of a trade become more valuable and influential with increases in geographic distance between backers and the innovator. Heretofore, no study has examined the interaction between geographic distance and quality signals. In study 1, using a sample of 102,179 Kickstarter crowdfunding campaigns launched in 156 different countries (i.e. creators are from 156 different countries), I show that quality signals including human capital, endorsement, preparedness, and positive psychological capital are more influential on the likelihood of success of crowdfunding campaigns that are collecting funds from more geographically remote backers than campaigns that are receiving funds from more geographically proximate backers. The results hold true even after controlling for cultural differences. Second, I investigate the role of less costly signals of quality and their interaction with traditional quality signals. I also examine their interaction with meaning in crowdfunding campaign narratives. Study 2 investigates the importance of textual description, its focus on reward/risk rhetoric, and its quality. Using a sample of 187,769 Kickstarter projects, I show that the meaning and quality of a project’s textual description can affect the success/failure of that project in securing funds and creating a market for the innovative idea. I show that textual quality and fluency functions as a less costly signal of preparedness, which can reduce the negative… Advisors/Committee Members: Pujari, Devashish, Business.

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Information security has been a crucial strategic issue in organizational management. Information security management (ISM) is a systematic process of effectively coping with information security threats and risks in an organization, through the application of a suitable range of physical, technical or operational security controls, to protect information assets and achieve business goals. There is a strong need for rigorous qualitative and quantitative empirical studies in the field of organizational information security management in order to better understand how to optimize the ISM process. Applying critical success factors approach, this study builds a theoretical model to investigate main factors that contribute to ISM success. The following tasks were carried out: (1) identify critical success factors of ISM performance; (2) build an ISM success model and develop related hypotheses; (3) develop construct measures for critical success factors and ISM performance evaluations; (4) collect data from the industry through interviews and surveys; and (5) empirically verify the model through quantitative analysis. The proposed theoretical model was empirically tested with data collected from a survey of managers who were presently involved with decision making regarding their company's information security (N=219). Overall, the theoretical model was successful in capturing the main antecedents of ISM performance. The results suggest that with business alignment, organizational support, IT competences, and organizational awareness of security risks and controls, information security controls can be effectively developed, resulting in successful information security management. This study contributes to the advancement of the information security management literature by (1) proposing a theoretical model to examine the effects of critical organizational success factors on the organization’s ISM performance, (2) empirically validating this proposed model, (3) developing and validating an ISM performance construct, and (4) reviewing the most influential information security management standards and trying to validate some basic guidelines of the standard.

Thesis

Doctor of Philosophy (PhD)

This thesis addresses three research questions: (1) How to measure ISM performance? (2) What are the critical factors that must be present to make ISM effective? And, (3) how do these factors contribute to the success of ISM? To the best of the researcher’s knowledge, this is the first known study to empirically investigate the most important factors for ISM success and their impact on ISM performance. This study contributes to the advancement of the information security management literature by (1) proposing a theoretical model to examine the effects of critical organizational success factors on the organization’s ISM performance, (2) empirically validating this proposed model, (3) developing and validating an ISM performance construct, and (4) reviewing the most influential information security management standards and…

Advisors/Committee Members: Yuan, Yufei, Business.

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This thesis examines important topics in corporate cash holdings and forecaster overconfidence. First, I provide an in-depth study of the interaction between intra-industry contagion risk and cash holdings. I develop a novel measure of a firm’s exposure to contagion risk that builds on the firm’s stock return comovement with other industry participants and separates contagion and competition effects caused by the expected financial distress of its industry peers. I show that high contagion-risk firms hold more cash because they face higher costs of external finance due to the potential decrease in their collateral values and the increased likelihood of their future financial distress caused by the net contagion effect. Second, in a co-authored paper with Drs. Jiaping Qiu and Chi Wan, we conduct a cross-country analysis to examine how financial development affects the reliance of corporate liquidity management on tangible capital. We find that financial development and better institutions lower the cash-tangibility sensitivity. This supports the view that financial development reduces the collateral role of tangible assets, thereby relaxing financial constraints of firms with low asset tangibility. This provides further firm-level evidence and sheds new light on the link between financial development and economic growth, as financial development promotes more efficient allocations of economic resources and hence facilitates investments and economic growth. Third, in a co-authored paper with Drs. Richard Deaves and Michael Schröder, we document using the ZEW panel of German stock market forecasters that weak forecasters tend to be overconfident in the sense that they provide extreme forecasts and their confidence intervals are less likely to contain eventual realizations. Moderate filters based on forecast accuracy over short rolling windows are somewhat successful in improving predictability. While poor performance can be due to various factors, a filter based on a prior tendency to provide extreme forecasts also improves predictability.

Thesis

Doctor of Philosophy (PhD)

Advisors/Committee Members: Deaves, Richard, Business.

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In this thesis, we focus on the applications of incentive mechanism design in operations and supply chain management (OSCM). Most significant – and interesting – topics arising in OSCM are concerned with the management of relationships among supply chain members under asymmetric information. Since the incentive mechanism design based on the principal-agent model deals with asymmetric information in a satisfactory way, it has become an important tool in investigating OSCM-related asymmetric information problems. We start with an introduction in Chapter 1. In this chapter, we briefly describe the theory of incentive mechanism design and its applications to OSCM, and the organization structure of this thesis. In Chapter 2, we study the optimal wage scheme and effort level in a contracting problem where both the principal and the agent are risk-averse. This chapter is a starting point for analyzing the buyer's optimal ordering decision and incentives for yield improvement in Chapters 3 and 4. Chapter 3 investigates the buyer's optimal ordering decision and incentives for yield improvement in the setting of random yield for the critical component and uncertain demand for the finished product. In Chapter 4, we assume the supplier's effort and yield become continuous and study a continuous optimization problem where the buyer decides the optimal order quantities and incentives for yield improvement under random demand. Our thesis ends with a conclusion and addresses the future research in Chapter 5.

Thesis

Doctor of Philosophy (PhD)

Advisors/Committee Members: Parlar, Mahmut, Business.

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In this dissertation, we study several stochastic capacity expansion models in the presence of permanent, spot market, and contract capacity for acquisition. Using a scenario tree approach to handle the data uncertainty of the problems, we develop multi-stage stochastic integer programming formulations for these models. First, we study multi-period single resource stochastic capacity expansion problems, where different sources of capacity are available to the decision maker. We develop efficient algorithms that can solve these models to optimality in polynomial time. Second, we study multi-period stochastic network capacity expansion problems with different sources for capacity. The proposed models are NP-hard multi-stage stochastic integer programs and we develop an efficient, asymptotically convergent approximation algorithm to solve them. Third, we consider some decomposition algorithms to solve the proposed multi-stage stochastic network capacity expansion problem. We propose an enhanced Benders' decomposition algorithm to solve the problem, and a Benders' decomposition-based heuristic algorithm to find tight bounds for it. Finally, we extend the stochastic network capacity expansion model by imposing budget restriction on permanent capacity acquisition cost. We design a Lagrangian relaxation algorithm to solve the model, including heuristic methods to find tight upper bounds for it.

Thesis

Doctor of Philosophy (PhD)

Advisors/Committee Members: Huang, Kai, Business.

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The broad purpose of this dissertation is to enhance the quality of managerial decisions through evidence-based management. Specifically, it raises three key questions: What is evidence? What are the attributes of knowledge that can facilitate informed decision making? How can such knowledge be generated? To answer these questions this thesis proposes a theory of evidence, suggesting that the strength of evidence is contingent upon its methodological fit, contextuality, transparency, replicability, and consensus. A model of evidence-based decision making is offered that explores how managers’ judgment, experience, and personal values along with the values of other stakeholders, contextual factors, and ethical constraints, may affect the decision process. Moreover, this thesis argues that in order to foster evidence-based management practice we need knowledge that is rigorous, relevant and actionable. To this end, a theory of actionability is proposed, and an empirical study is conducted to determine the attributes of actionable management knowledge. Based on the study, an actionability index is suggested. Evidence that is actionable requires sustainable collaborative effort to produce, curate and communicate. To accomplish that a theory of evidence-based collaboration is proposed. This theory conceives the collaboration as an independent organization that oversees the process of bringing rigour, relevance, and actionability together, and provides an interactive platform for producers, arbiters and users of management knowledge to communicate and collaborate. A template, guided by the theory of collaboration, is designed to produce systematic reviews that are useful for management practice.

Dissertation

Doctor of Philosophy (PhD)

Advisors/Committee Members: Baba, Vishwanath, Business.

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We propose a classification framework for the operations management literature that has looked at pricing and ordering in supply chains when supply and/or demand are uncertain. We then focus on developing three new models for managing supply and demand uncertainties in supply chains. In the first model, we study a two period sourcing problem of a firm under two sets of contracts. The contracts differ in terms of acquisition costs and the level of risk that they impose on the firm. We provide the conditions where the optimum solution is unique and also explore the behaviour of the optimum solution analytically and numerically. One application of our model is in the agribusiness supply chain and we provide numerical examples based on data from the almond industry in California. In the second model we look at a joint ordering, pricing and capacity planning problem. We characterize the optimum policy both in single and multi-period cases. In addition, we study the impact of fixed production costs on the optimum policy. The third model is devoted to coordination between a buyer and a supplier where there is a possibility of improving the supplier by both players. We analyze the problem under a Stackelberg game setting where the buyer is the leader. We show that the buyer either tries to amplify the investment of the supplier by order inflation or assumes all the investment costs. We investigate the behaviour of the optimum solution under different strategies.

Thesis

Doctor of Philosophy (PhD)

Advisors/Committee Members: Hassini, Elkafi, Business.

▼ In this dissertation, my focus is on understanding distribution channel conflict, its relationship with efficient channel governance and its impact on channel performance. In particular, I will study (1) how the channel conflict can be defined and interpreted, (2) how channel conflict can affect channel governance, (3) what would be the performance outcomes of channel conflict, and (4) how channel conflict can be managed. My theoretical frameworks borrow mainly from transaction cost economics theory (TCE), and strategic marketing. On the empirical side, I employ several methods including meta-analysis (Two-Stage SEM) as well as different econometrics techniques such as Conditional Mixed-Process (CMP) regression estimation. My data comes from diverse sources and are mainly hand collected and created from archival sources. For the meta-analysis study, I extract empirical results of more than 100 studies on channel conflict since the 1960s. For the other empirical efforts, the data comes from various sources. The major data collection undertakings include extracting and integrating data from: (1) Franchise Disclosure Document (FDD) of more than 1000 franchise firms, (2) firms records, and (3) specific franchise rankings such as Entrepreneur and Franchise Times’ rankings spanning from 2004 to 2015. The dissertation comprises following broad inter-related chapters (excluding Introduction and Conclusion chapters): (1) Managing Channel Conflict: Insights from the Current Literature, (2) Conflict and Performance in Channels: A Meta-Analysis, (3) Channel Conflict: Bad for Business?, (4) Adapting to Channel Conflict: An Empirical Study?, and (5) Two Views on Channel Conflict. Chapter 1 is a compendium on channel conflict that not only provides a comprehensive literature review on channel conflict (since the 1960s) but also identifies gaps and provides some managerial perspectives on channel conflict. One of the identified gaps in Chapter 1 revolves around the role of channel conflict and its relationship with other inter-firm constructs. In Chapter 2, I build on this identified gap by conducting a comprehensive meta-analysis study using Two-Stage SEM (TSSEM) method to aggregate the previous findings on channel conflict and its relationship with other inter-firm constructs particularly channel performance. I also investigate the potential moderators of the conflict-performance link. Chapters 1 and 2 set the stage for the next empirical work. One of the enduring debates in the channel domain is about the functionality and dysfunctionality of channel conflict. In Chapter 3, I address this directly by exploring the non-linear (inverted U-shaped) relationship between channel conflict and performance. While Chapter 3 explores the empirical relation between conflict and performance, another understudied but important research question is about how firms react to channel conflict. Such reactions can span the range from relying on relational norms to more explicit adjustment in channel governance. In Chapter… Advisors/Committee Members: Ray, Sourav, Business Administration.